Physicists define climate as a “complex system”. While there are a lot of interpretations about it, in this specific case we can consider “complex” to be “unsolvable in analytical ways”.
This may seems discouraging, but it actually paves the way to a wide range of numerical algorithms that aim to solve the climate challenges. With the computational developments of the last years, Machine Learning algorithms are certainly part of them.
The challenge I want to discuss is based on forecasting the average temperature using traditional machine learning algorithms: Auto Regressive Integrated Moving Average models (ARIMA).